Our work provides an insight in volatility-based portfolio switching and calculating the returns in the event of rule based portfolio allocation. we have selected four indices namely:

Adding libraries

EQUITY

Function for getting closed price

We have selected historical volatility for our study as it will easier for investment decision makers to comprehend as historical data is readily available.

Testing volatility Scenarios

We have converted historical volatility for simpler comprehension and binning for impletmentation of rules.

We have taken five scenarios where we define different volatility levels based on variance of historical volatility dataframe and check for condition where succesive days volatility has breached previous days volatilty by a particular margin.

Since these values are arbitrary, investors are free to define their volatility levels for switching.

The exihibit below shows number of times volatility has breached the above condtions in the given investment horizon.

For ^FTSE

CASE 1

CASE 2

CASE 3

CASE 4

CASE 5

FOR ^GSPC

CASE 1

CASE 2

CASE 3

CASE 4

CASE 5

FOR ^HSI

CASE 1

CASE 2

CASE 3

CASE 4

CASE 5

FOR ^NSEI

CASE 1

CASE 2

CASE 3

CASE 4

CASE 5

FOR GLD

CASE 1

CASE 2

CASE 3

CASE 4

CASE 5

BOND DATA

FOR UK BOND

CASE 1

CASE 2

CASE 3

CASE 4

CASE 5

EQUITY

BOND

FOR UNITED STATES

CASE 1

CASE 2

CASE 3

CASE 4

CASE 5

EQUITY

BOND

FOR INDIA

CASE 1

CASE 2

CASE 3

CASE 4

CASE 5

EQUITY

BOND

FOR CHINA

CASE 1

CASE 2

CASE 3

CASE 4

CASE 5

EQUITY

BOND

Returns of an investments of $1000000 from different markets

APPENDIX: COVID-19 ANALYSIS SUMMARY

Cumulative returns during Pandemic year of 2020

Equity

Bond